{ "cells": [ { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import tweepy\n", "import pandas as pd\n", "import json\n", "\n", "import seaborn as sns\n", "import matplotlib.pyplot as plt\n", "\n", "%matplotlib inline" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Gute Referenz, der ich den meisten Code für den Datendownload verdanke:\n", "https://www.packtpub.com/big-data-and-business-intelligence/mastering-social-media-mining-python. \n", "\n", "Falls der Code selbst ausgeführt werden soll, müssen hier die eigenen Twitter-Keys verwendet werden. Details siehe auch in der Referenz oben." ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": true }, "outputs": [], "source": [ "consumer_key = 'XXX'\n", "consumer_secret = 'XXX'\n", "access_token = 'XXX'\n", "access_secret = 'XXX'" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": false }, "outputs": [], "source": [ "auth = tweepy.OAuthHandler(consumer_key, consumer_secret) \n", "auth.set_access_token(access_token, access_secret) " ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": false }, "outputs": [], "source": [ "client = tweepy.API(auth, wait_on_rate_limit=True)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": true }, "outputs": [], "source": [ "users = ('derStandardat', 'KURIERat', 'ArminWolf', 'SPIEGEL_Top')\n", "# last tweet from @diepresse_com in 2012\n", "# last tweet from @oe24News in April 2016" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Herunterladen der Tweets\n", "Da derStandard.at mit dem 2016-10-26 das 3.200 Tweet Limit der Twitter API erreicht, lade ich nur Nov und Dez herunter" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "getting data for derStandardat\n", "getting data for KURIERat\n", "getting data for ArminWolf\n", "getting data for SPIEGEL_Top\n" ] } ], "source": [ "for user in users:\n", " print('getting data for {}'.format(user))\n", " fname = \"user_timeline_{}.jsonl\".format(user) \n", " with open(fname, 'w') as f: \n", " for page in tweepy.Cursor(client.user_timeline, screen_name=user, count=200).pages(16): \n", " for status in page: \n", " if (status.created_at.year == 2016) & (status.created_at.month > 10):\n", " f.write(json.dumps(status._json)+\"\\n\") \n", " else:\n", " break" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Tweets in Datenframe zusammenfassen" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "collapsed": false }, "outputs": [], "source": [ "tweets = [pd.read_json(fname, lines=True) for fname in [\"user_timeline_{}.jsonl\".format(user) for user in users]]\n", "df = pd.concat(tweets).reset_index(drop=True)" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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0 | \n", "NaN | \n", "NaN | \n", "2016-12-31 21:30:09 | \n", "{'hashtags': [], 'urls': [{'expanded_url': 'ht... | \n", "NaN | \n", "0 | \n", "False | \n", "NaN | \n", "815309091266592768 | \n", "815309091266592768 | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "0 | \n", "False | \n", "NaN | \n", "<a href=\"http://swat.io\" rel=\"nofollow\">Swat.i... | \n", "Rund 10 Prozent der Österreicher \"schwänzen\" h... | \n", "False | \n", "{'profile_background_tile': False, 'is_transla... | \n", "
1 | \n", "NaN | \n", "NaN | \n", "2016-12-31 21:00:22 | \n", "{'hashtags': [], 'urls': [{'expanded_url': 'ht... | \n", "NaN | \n", "1 | \n", "False | \n", "NaN | \n", "815301597106491396 | \n", "815301597106491392 | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "2 | \n", "False | \n", "NaN | \n", "<a href=\"http://swat.io\" rel=\"nofollow\">Swat.i... | \n", "Anderswo ist schon seit Stunden 2017. So feier... | \n", "False | \n", "{'profile_background_tile': False, 'is_transla... | \n", "
2 | \n", "NaN | \n", "NaN | \n", "2016-12-31 20:30:09 | \n", "{'hashtags': [], 'urls': [{'expanded_url': 'ht... | \n", "NaN | \n", "2 | \n", "False | \n", "NaN | \n", "815293991151370240 | \n", "815293991151370240 | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "5 | \n", "False | \n", "NaN | \n", "<a href=\"http://swat.io\" rel=\"nofollow\">Swat.i... | \n", "\"Zweifel an menschenwürdiger Unterbringung\": B... | \n", "False | \n", "{'profile_background_tile': False, 'is_transla... | \n", "
3 rows × 29 columns
\n", "\n", " | contributors_enabled | \n", "created_at | \n", "default_profile | \n", "default_profile_image | \n", "description | \n", "entities | \n", "favourites_count | \n", "follow_request_sent | \n", "followers_count | \n", "following | \n", "... | \n", "profile_text_color | \n", "profile_use_background_image | \n", "protected | \n", "screen_name | \n", "statuses_count | \n", "time_zone | \n", "translator_type | \n", "url | \n", "utc_offset | \n", "verified | \n", "
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | \n", "False | \n", "Fri Mar 06 16:43:22 +0000 2009 | \n", "False | \n", "False | \n", "Aus dem Newsroom der österreichischen Tageszei... | \n", "{'description': {'urls': [{'expanded_url': 'ht... | \n", "2884 | \n", "False | \n", "246282 | \n", "False | \n", "... | \n", "000000 | \n", "True | \n", "False | \n", "derStandardat | \n", "67690 | \n", "Vienna | \n", "none | \n", "http://t.co/0N5NEkJcaI | \n", "3600 | \n", "True | \n", "
1 | \n", "False | \n", "Fri Mar 06 16:43:22 +0000 2009 | \n", "False | \n", "False | \n", "Aus dem Newsroom der österreichischen Tageszei... | \n", "{'description': {'urls': [{'expanded_url': 'ht... | \n", "2884 | \n", "False | \n", "246282 | \n", "False | \n", "... | \n", "000000 | \n", "True | \n", "False | \n", "derStandardat | \n", "67690 | \n", "Vienna | \n", "none | \n", "http://t.co/0N5NEkJcaI | \n", "3600 | \n", "True | \n", "
2 rows × 42 columns
\n", "\n", " | name | \n", "followers_count | \n", "
---|---|---|
5564 | \n", "Armin Wolf | \n", "323854 | \n", "
7836 | \n", "SPIEGEL ONLINE Top | \n", "280554 | \n", "
0 | \n", "derStandard.at | \n", "246282 | \n", "
2981 | \n", "KURIER | \n", "69563 | \n", "
\n", " | contributors | \n", "coordinates | \n", "created_at | \n", "entities | \n", "extended_entities | \n", "favorite_count | \n", "favorited | \n", "geo | \n", "id | \n", "id_str | \n", "... | \n", "quoted_status_id | \n", "quoted_status_id_str | \n", "retweet_count | \n", "retweeted | \n", "retweeted_status | \n", "source | \n", "text | \n", "truncated | \n", "user | \n", "name | \n", "
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
9626 | \n", "NaN | \n", "NaN | \n", "2016-11-01 00:27:19 | \n", "{'hashtags': [], 'urls': [{'expanded_url': 'ht... | \n", "NaN | \n", "0 | \n", "False | \n", "NaN | \n", "793248015691685889 | \n", "793248015691685888 | \n", "... | \n", "NaN | \n", "NaN | \n", "1 | \n", "False | \n", "NaN | \n", "<a href=\"http://ifttt.com\" rel=\"nofollow\">IFTT... | \n", "71 Jahre nach seinem Verschwinden: Schweden er... | \n", "False | \n", "{'profile_background_tile': False, 'is_transla... | \n", "SPIEGEL ONLINE Top | \n", "
9625 | \n", "NaN | \n", "NaN | \n", "2016-11-01 00:42:44 | \n", "{'hashtags': [], 'urls': [{'expanded_url': 'ht... | \n", "NaN | \n", "0 | \n", "False | \n", "NaN | \n", "793251895787872257 | \n", "793251895787872256 | \n", "... | \n", "NaN | \n", "NaN | \n", "0 | \n", "False | \n", "NaN | \n", "<a href=\"http://ifttt.com\" rel=\"nofollow\">IFTT... | \n", "Silvio Gazzaniga: Designer des WM-Pokals ist t... | \n", "False | \n", "{'profile_background_tile': False, 'is_transla... | \n", "SPIEGEL ONLINE Top | \n", "
9624 | \n", "NaN | \n", "NaN | \n", "2016-11-01 05:17:19 | \n", "{'hashtags': [], 'urls': [{'expanded_url': 'ht... | \n", "NaN | \n", "1 | \n", "False | \n", "NaN | \n", "793320994966495234 | \n", "793320994966495232 | \n", "... | \n", "NaN | \n", "NaN | \n", "2 | \n", "False | \n", "NaN | \n", "<a href=\"http://ifttt.com\" rel=\"nofollow\">IFTT... | \n", "+++ Der Morgen live +++: Wirtschaftsminister G... | \n", "False | \n", "{'profile_background_tile': False, 'is_transla... | \n", "SPIEGEL ONLINE Top | \n", "
3 rows × 30 columns
\n", "name | \n", "Armin Wolf | \n", "KURIER | \n", "SPIEGEL ONLINE Top | \n", "derStandard.at | \n", "
---|---|---|---|---|
retweeted_status | \n", "\n", " | \n", " | \n", " | \n", " |
False | \n", "1961.0 | \n", "2520.0 | \n", "1791.0 | \n", "2957.0 | \n", "
True | \n", "311.0 | \n", "63.0 | \n", "NaN | \n", "24.0 | \n", "
name | \n", "Armin Wolf | \n", "KURIER | \n", "SPIEGEL ONLINE Top | \n", "derStandard.at | \n", "
---|---|---|---|---|
retweeted_status | \n", "\n", " | \n", " | \n", " | \n", " |
False | \n", "1961 | \n", "2520 | \n", "1791 | \n", "2957 | \n", "
\n", " | Mo | \n", "Di | \n", "Mi | \n", "Do | \n", "Fr | \n", "Sa | \n", "So | \n", "
---|---|---|---|---|---|---|---|
name | \n", "\n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " |
Armin Wolf | \n", "226 | \n", "239 | \n", "458 | \n", "315 | \n", "316 | \n", "151 | \n", "256 | \n", "
KURIER | \n", "346 | \n", "452 | \n", "440 | \n", "429 | \n", "385 | \n", "233 | \n", "235 | \n", "
SPIEGEL ONLINE Top | \n", "242 | \n", "289 | \n", "267 | \n", "266 | \n", "335 | \n", "190 | \n", "202 | \n", "
derStandard.at | \n", "439 | \n", "491 | \n", "496 | \n", "489 | \n", "469 | \n", "290 | \n", "283 | \n", "
created_at | \n", "0 | \n", "1 | \n", "2 | \n", "3 | \n", "4 | \n", "5 | \n", "6 | \n", "7 | \n", "8 | \n", "9 | \n", "... | \n", "14 | \n", "15 | \n", "16 | \n", "17 | \n", "18 | \n", "19 | \n", "20 | \n", "21 | \n", "22 | \n", "23 | \n", "
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
name | \n", "\n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " |
Armin Wolf | \n", "24.0 | \n", "15.0 | \n", "10.0 | \n", "15.0 | \n", "13.0 | \n", "34.0 | \n", "43.0 | \n", "58.0 | \n", "105.0 | \n", "150.0 | \n", "... | \n", "111.0 | \n", "115.0 | \n", "155.0 | \n", "109.0 | \n", "73.0 | \n", "49.0 | \n", "84.0 | \n", "118.0 | \n", "92.0 | \n", "85.0 | \n", "
KURIER | \n", "7.0 | \n", "2.0 | \n", "1.0 | \n", "4.0 | \n", "3.0 | \n", "216.0 | \n", "128.0 | \n", "179.0 | \n", "150.0 | \n", "192.0 | \n", "... | \n", "169.0 | \n", "127.0 | \n", "103.0 | \n", "145.0 | \n", "110.0 | \n", "96.0 | \n", "79.0 | \n", "20.0 | \n", "9.0 | \n", "7.0 | \n", "
SPIEGEL ONLINE Top | \n", "25.0 | \n", "16.0 | \n", "27.0 | \n", "23.0 | \n", "21.0 | \n", "51.0 | \n", "78.0 | \n", "104.0 | \n", "80.0 | \n", "96.0 | \n", "... | \n", "117.0 | \n", "117.0 | \n", "127.0 | \n", "102.0 | \n", "72.0 | \n", "78.0 | \n", "78.0 | \n", "53.0 | \n", "42.0 | \n", "35.0 | \n", "
3 rows × 24 columns
\n", "created_at | \n", "0 | \n", "1 | \n", "2 | \n", "3 | \n", "4 | \n", "5 | \n", "6 | \n", "7 | \n", "8 | \n", "9 | \n", "... | \n", "14 | \n", "15 | \n", "16 | \n", "17 | \n", "18 | \n", "19 | \n", "20 | \n", "21 | \n", "22 | \n", "23 | \n", "
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Mo | \n", "2.0 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "4.0 | \n", "3.0 | \n", "11.0 | \n", "21.0 | \n", "... | \n", "4.0 | \n", "12.0 | \n", "12.0 | \n", "7.0 | \n", "9.0 | \n", "1.0 | \n", "15.0 | \n", "28.0 | \n", "17.0 | \n", "25.0 | \n", "
Di | \n", "NaN | \n", "3.0 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "4.0 | \n", "13.0 | \n", "18.0 | \n", "23.0 | \n", "... | \n", "8.0 | \n", "9.0 | \n", "13.0 | \n", "2.0 | \n", "8.0 | \n", "7.0 | \n", "5.0 | \n", "23.0 | \n", "8.0 | \n", "11.0 | \n", "
Mi | \n", "11.0 | \n", "12.0 | \n", "7.0 | \n", "15.0 | \n", "5.0 | \n", "11.0 | \n", "11.0 | \n", "19.0 | \n", "30.0 | \n", "44.0 | \n", "... | \n", "27.0 | \n", "26.0 | \n", "19.0 | \n", "19.0 | \n", "21.0 | \n", "4.0 | \n", "13.0 | \n", "25.0 | \n", "13.0 | \n", "13.0 | \n", "
Do | \n", "9.0 | \n", "NaN | \n", "2.0 | \n", "NaN | \n", "NaN | \n", "6.0 | \n", "11.0 | \n", "3.0 | \n", "16.0 | \n", "9.0 | \n", "... | \n", "15.0 | \n", "17.0 | \n", "40.0 | \n", "28.0 | \n", "4.0 | \n", "11.0 | \n", "18.0 | \n", "11.0 | \n", "23.0 | \n", "17.0 | \n", "
Fr | \n", "NaN | \n", "NaN | \n", "1.0 | \n", "NaN | \n", "8.0 | \n", "17.0 | \n", "11.0 | \n", "18.0 | \n", "20.0 | \n", "23.0 | \n", "... | \n", "33.0 | \n", "18.0 | \n", "45.0 | \n", "13.0 | \n", "14.0 | \n", "8.0 | \n", "10.0 | \n", "2.0 | \n", "8.0 | \n", "4.0 | \n", "
Sa | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "2.0 | \n", "NaN | \n", "8.0 | \n", "10.0 | \n", "... | \n", "16.0 | \n", "16.0 | \n", "12.0 | \n", "7.0 | \n", "3.0 | \n", "2.0 | \n", "5.0 | \n", "NaN | \n", "2.0 | \n", "5.0 | \n", "
So | \n", "2.0 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "2.0 | \n", "2.0 | \n", "20.0 | \n", "... | \n", "8.0 | \n", "17.0 | \n", "14.0 | \n", "33.0 | \n", "14.0 | \n", "16.0 | \n", "18.0 | \n", "29.0 | \n", "21.0 | \n", "10.0 | \n", "
7 rows × 24 columns
\n", "\n", " | created_at | \n", "0 | \n", "1 | \n", "2 | \n", "3 | \n", "4 | \n", "5 | \n", "6 | \n", "7 | \n", "8 | \n", "9 | \n", "... | \n", "14 | \n", "15 | \n", "16 | \n", "17 | \n", "18 | \n", "19 | \n", "20 | \n", "21 | \n", "22 | \n", "23 | \n", "
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
created_at | \n", "created_at | \n", "\n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " |
11 | \n", "1 | \n", "2.0 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "2.0 | \n", "4.0 | \n", "21.0 | \n", "10.0 | \n", "8.0 | \n", "... | \n", "4.0 | \n", "7.0 | \n", "4.0 | \n", "5.0 | \n", "5.0 | \n", "9.0 | \n", "7.0 | \n", "6.0 | \n", "3.0 | \n", "NaN | \n", "
2 | \n", "1.0 | \n", "NaN | \n", "1.0 | \n", "NaN | \n", "1.0 | \n", "15.0 | \n", "8.0 | \n", "8.0 | \n", "7.0 | \n", "12.0 | \n", "... | \n", "9.0 | \n", "7.0 | \n", "7.0 | \n", "5.0 | \n", "9.0 | \n", "5.0 | \n", "5.0 | \n", "8.0 | \n", "2.0 | \n", "1.0 | \n", "|
3 | \n", "1.0 | \n", "1.0 | \n", "1.0 | \n", "NaN | \n", "2.0 | \n", "8.0 | \n", "9.0 | \n", "4.0 | \n", "8.0 | \n", "11.0 | \n", "... | \n", "10.0 | \n", "9.0 | \n", "8.0 | \n", "18.0 | \n", "8.0 | \n", "4.0 | \n", "6.0 | \n", "3.0 | \n", "6.0 | \n", "2.0 | \n", "
3 rows × 24 columns
\n", "\n", " | created_at | \n", "0 | \n", "1 | \n", "2 | \n", "3 | \n", "4 | \n", "5 | \n", "6 | \n", "7 | \n", "8 | \n", "9 | \n", "... | \n", "14 | \n", "15 | \n", "16 | \n", "17 | \n", "18 | \n", "19 | \n", "20 | \n", "21 | \n", "22 | \n", "23 | \n", "
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
created_at | \n", "created_at | \n", "\n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " |
11 | \n", "1 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "2.0 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
2 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "1.0 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "... | \n", "1.0 | \n", "1.0 | \n", "2.0 | \n", "NaN | \n", "1.0 | \n", "NaN | \n", "NaN | \n", "2.0 | \n", "NaN | \n", "NaN | \n", "|
3 | \n", "NaN | \n", "NaN | \n", "1.0 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "... | \n", "1.0 | \n", "1.0 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "2.0 | \n", "NaN | \n", "
3 rows × 24 columns
\n", "\n", " | created_at | \n", "text | \n", "
---|---|---|
7664 | \n", "2016-11-09 03:00:17 | \n", "Oje. https://t.co/jg5LpILcXl | \n", "
7663 | \n", "2016-11-09 03:00:26 | \n", "@RalphJanik Eh. | \n", "
7662 | \n", "2016-11-09 03:06:42 | \n", "@pitgottschalk Ernste Frage? Der ganz links. | \n", "
7661 | \n", "2016-11-09 03:11:24 | \n", "Die jüngste NYT-Prognose: Demnach würde Clinto... | \n", "
7660 | \n", "2016-11-09 03:14:06 | \n", "US-Präsidenten ohne Stimmenmehrheit (popular v... | \n", "
7659 | \n", "2016-11-09 03:21:15 | \n", "@EvaGauda US-Wahlsystem googeln. Tausendfach s... | \n", "
7658 | \n", "2016-11-09 03:26:33 | \n", "Trump gewinnt Ohio, sagt CNN. Das ist wirklich... | \n", "
7657 | \n", "2016-11-09 03:28:39 | \n", "@StefanHaboeck Das ist die Auszählung. Beziehe... | \n", "
7656 | \n", "2016-11-09 03:28:52 | \n", "@TOMK1988 Nicht immer. Aber häufig. | \n", "
7655 | \n", "2016-11-09 03:31:42 | \n", "So einen Wahlabend habe ich noch nie gesehen. ... | \n", "
7654 | \n", "2016-11-09 03:36:47 | \n", "Jetzt hat auch Nate Silver Trump als Favoriten... | \n", "
7653 | \n", "2016-11-09 03:38:25 | \n", "Wenn das alles hält, gibt es einen Präsidenten... | \n", "
7652 | \n", "2016-11-09 03:39:54 | \n", "@TOMK1988 1960 glaube ich. Da gewann Nixon Ohi... | \n", "
7647 | \n", "2016-11-09 03:49:12 | \n", "Dabei hätte das nach dem Debakel von 2000 nie ... | \n", "
7643 | \n", "2016-11-09 03:54:16 | \n", "Wenn Clinton jetzt nicht Pennsylvania + Michig... | \n", "
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---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
created_at | \n", "created_at | \n", "\n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " |
11 | \n", "1 | \n", "1.0 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "3.0 | \n", "7.0 | \n", "33.0 | \n", "15.0 | \n", "23.0 | \n", "... | \n", "1.0 | \n", "15.0 | \n", "18.0 | \n", "14.0 | \n", "39.0 | \n", "30.0 | \n", "23.0 | \n", "7.0 | \n", "7.0 | \n", "NaN | \n", "
2 | \n", "4.0 | \n", "NaN | \n", "1.0 | \n", "NaN | \n", "4.0 | \n", "9.0 | \n", "18.0 | \n", "10.0 | \n", "14.0 | \n", "8.0 | \n", "... | \n", "12.0 | \n", "6.0 | \n", "24.0 | \n", "6.0 | \n", "10.0 | \n", "4.0 | \n", "9.0 | \n", "4.0 | \n", "5.0 | \n", "12.0 | \n", "|
3 | \n", "0.0 | \n", "1.0 | \n", "21.0 | \n", "NaN | \n", "8.0 | \n", "24.0 | \n", "7.0 | \n", "3.0 | \n", "6.0 | \n", "15.0 | \n", "... | \n", "12.0 | \n", "7.0 | \n", "9.0 | \n", "16.0 | \n", "14.0 | \n", "6.0 | \n", "13.0 | \n", "4.0 | \n", "10.0 | \n", "155.0 | \n", "
3 rows × 24 columns
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---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
created_at | \n", "created_at | \n", "\n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " | \n", " |
11 | \n", "1 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "... | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "9.0 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
2 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "4.0 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "... | \n", "0.0 | \n", "5.0 | \n", "13.0 | \n", "NaN | \n", "0.0 | \n", "NaN | \n", "NaN | \n", "0.0 | \n", "NaN | \n", "NaN | \n", "|
3 | \n", "NaN | \n", "NaN | \n", "21.0 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "... | \n", "6.0 | \n", "0.0 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "8.0 | \n", "NaN | \n", "
3 rows × 24 columns
\n", "" ], "text/plain": [ "created_at 0 1 2 3 4 5 6 7 8 9 ... 14 \\\n", "created_at created_at ... \n", "11 1 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN ... NaN \n", " 2 NaN NaN NaN NaN 4.0 NaN NaN NaN NaN NaN ... 0.0 \n", " 3 NaN NaN 21.0 NaN NaN NaN NaN NaN NaN NaN ... 6.0 \n", "\n", "created_at 15 16 17 18 19 20 21 22 23 \n", "created_at created_at \n", "11 1 NaN NaN NaN NaN 9.0 NaN NaN NaN NaN \n", " 2 5.0 13.0 NaN 0.0 NaN NaN 0.0 NaN NaN \n", " 3 0.0 NaN NaN NaN NaN NaN NaN 8.0 NaN \n", "\n", "[3 rows x 24 columns]" ] }, "execution_count": 59, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_temp = df[df.name == 'Armin Wolf'].groupby([df.created_at.dt.month, df.created_at.dt.day, \n", " df.created_at.dt.hour])['retweet_count'].sum().unstack()\n", "df_temp[:3]" ] }, { "cell_type": "code", "execution_count": 60, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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M0tJSREdH48iRIygqKoKPj4/Ctcmfk6oxu3x3NcdxeOedd9SuR23j0zOdO3cO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\nd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"text/plain": [ "\n", " | 0 | \n", "1 | \n", "2 | \n", "3 | \n", "4 | \n", "
---|---|---|---|---|---|
9619 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
2980 | \n", "putin | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
5563 | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
\n", " | contributors | \n", "coordinates | \n", "created_at | \n", "entities | \n", "extended_entities | \n", "favorite_count | \n", "favorited | \n", "geo | \n", "id | \n", "id_str | \n", "... | \n", "text | \n", "truncated | \n", "user | \n", "name | \n", "hashtags_list | \n", "0 | \n", "1 | \n", "2 | \n", "3 | \n", "4 | \n", "
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
9619 | \n", "NaN | \n", "NaN | \n", "2016-11-01 06:47:27 | \n", "{'hashtags': [], 'urls': [{'expanded_url': 'ht... | \n", "NaN | \n", "1 | \n", "False | \n", "NaN | \n", "793343678643331072 | \n", "793343678643331072 | \n", "... | \n", "Haushaltskrise: Saudischer Finanzminister nach... | \n", "False | \n", "{'profile_background_tile': False, 'is_transla... | \n", "SPIEGEL ONLINE Top | \n", "[] | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
2980 | \n", "NaN | \n", "NaN | \n", "2016-11-01 07:00:17 | \n", "{'hashtags': [{'text': 'Putin', 'indices': [33... | \n", "NaN | \n", "1 | \n", "False | \n", "NaN | \n", "793346910333575168 | \n", "793346910333575168 | \n", "... | \n", "Der russische Präsident Wladimir #Putin setzt ... | \n", "False | \n", "{'profile_background_tile': False, 'is_transla... | \n", "derStandard.at | \n", "[putin] | \n", "putin | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
5563 | \n", "NaN | \n", "NaN | \n", "2016-11-01 07:00:25 | \n", "{'hashtags': [], 'urls': [], 'symbols': [], 'u... | \n", "NaN | \n", "1 | \n", "False | \n", "NaN | \n", "793346944131293184 | \n", "793346944131293184 | \n", "... | \n", "Guten Morgen aus dem KURIER Newsroom. @Juergen... | \n", "False | \n", "{'profile_background_tile': False, 'is_transla... | \n", "KURIER | \n", "[] | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "NaN | \n", "
3 rows × 36 columns
\n", "\n", " | id_str | \n", "name | \n", "hashtag_nr | \n", "hashtag | \n", "
---|---|---|---|---|
8 | \n", "793346910333575168 | \n", "derStandard.at | \n", "0 | \n", "putin | \n", "
25 | \n", "793354418855022592 | \n", "derStandard.at | \n", "0 | \n", "wissenschaft | \n", "
29 | \n", "793362107639226368 | \n", "derStandard.at | \n", "0 | \n", "smartphone | \n", "